Upload app.py

app.py

@@ -0,0 +1,161 @@
+import os
+import gradio as gr
+import requests
+import pandas as pd
+from smolagents import CodeAgent, DuckDuckGoSearchTool
+
+DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
+
+class HfApiModel:
+    def __init__(self, model_name="tiiuae/falcon-7b-instruct", api_key=None):
+        self.model_name = model_name
+        self.api_key = api_key or os.getenv("HF_TOKEN")
+        if not self.api_key:
+            raise ValueError("HF_TOKEN environment variable is missing.")
+
+    def __call__(self, prompt):
+        # Convert ChatMessage or list of ChatMessages to plain string
+        if hasattr(prompt, "content"):
+            prompt = prompt.content
+        elif isinstance(prompt, list):
+            prompt = " ".join(
+                m.content if hasattr(m, "content") else str(m) for m in prompt
+            )
+        else:
+            prompt = str(prompt)
+
+        url = f"https://api-inference.huggingface.co/models/{self.model_name}"
+        headers = {"Authorization": f"Bearer {self.api_key}"}
+        payload = {
+            "inputs": prompt,
+            "options": {"wait_for_model": True}
+        }
+
+        response = requests.post(url, headers=headers, json=payload, timeout=60)
+        response.raise_for_status()
+        output = response.json()
+
+        try:
+            return output[0]["generated_text"]
+        except Exception:
+            return f"ERROR: {output}"
+
+    def generate(self, prompt, **kwargs):
+        return self.__call__(prompt)
+
+class BasicAgent:
+    def __init__(self):
+        print("✅ BasicAgent initialized.")
+        self.agent = CodeAgent(
+            tools=[DuckDuckGoSearchTool()],
+            model=HfApiModel(model_name="tiiuae/falcon-7b-instruct")
+        )
+
+        SYSTEM_PROMPT = """You are a general AI assistant. I will ask you a question. Report your thoughts, and
+finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER].
+YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated
+list of numbers and/or strings.
+If you are asked for a number, don't use comma to write your number neither use units such as $ or
+percent sign unless specified otherwise.
+If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the
+digits in plain text unless specified otherwise.
+If you are asked for a comma separated list, apply the above rules depending of whether the element
+to be put in the list is a number or a string.
+"""
+        self.agent.prompt_templates["system_prompt"] += SYSTEM_PROMPT
+
+    def __call__(self, question: str) -> str:
+        print(f"📥 Agent received question: {question[:60]}...")
+        final_answer = self.agent.run(question)
+        print(f"📤 Agent returning answer: {final_answer}")
+        return final_answer
+
+def run_and_submit_all(profile: gr.OAuthProfile | None):
+    space_id = os.getenv("SPACE_ID")
+
+    if profile:
+        username = profile.username
+        print(f"🔐 Logged in as: {username}")
+    else:
+        return "⚠️ Please login with Hugging Face to continue.", None
+
+    questions_url = f"{DEFAULT_API_URL}/questions"
+    submit_url = f"{DEFAULT_API_URL}/submit"
+
+    try:
+        agent = BasicAgent()
+    except Exception as e:
+        return f"❌ Agent initialization failed: {e}", None
+
+    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main" if space_id else "Unknown"
+
+    try:
+        response = requests.get(questions_url, timeout=15)
+        response.raise_for_status()
+        questions_data = response.json()
+        if not questions_data:
+            return "❌ No questions received from the server.", None
+    except Exception as e:
+        return f"❌ Failed to fetch questions: {e}", None
+
+    answers_payload = []
+    results_log = []
+
+    for item in questions_data:
+        task_id = item.get("task_id")
+        question_text = item.get("question")
+        if not task_id or question_text is None:
+            continue
+        try:
+            submitted_answer = agent(question_text)
+        except Exception as e:
+            submitted_answer = f"AGENT ERROR: {e}"
+        answers_payload.append({
+            "task_id": task_id,
+            "submitted_answer": submitted_answer
+        })
+        results_log.append({
+            "Task ID": task_id,
+            "Question": question_text,
+            "Submitted Answer": submitted_answer
+        })
+
+    if not answers_payload:
+        return "⚠️ Agent failed to generate any answers.", pd.DataFrame(results_log)
+
+    submission_data = {
+        "username": username.strip(),
+        "agent_code": agent_code,
+        "answers": answers_payload
+    }
+
+    try:
+        response = requests.post(submit_url, json=submission_data, timeout=60)
+        response.raise_for_status()
+        result_data = response.json()
+        status = (
+            f"✅ Submission Successful!\n"
+            f"User: {result_data.get('username')}\n"
+            f"Score: {result_data.get('score', '?')}% "
+            f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')})\n"
+            f"Message: {result_data.get('message', 'No message.')}"
+        )
+        return status, pd.DataFrame(results_log)
+    except Exception as e:
+        return f"❌ Submission failed: {e}", pd.DataFrame(results_log)
+
+# Gradio UI
+with gr.Blocks() as demo:
+    gr.Markdown("# 🤖 Basic Agent Evaluation Runner")
+    gr.Markdown("Clone this space, log in, and run your agent on the questions. Modify `BasicAgent` logic if needed.")
+
+    gr.LoginButton()
+    run_button = gr.Button("▶️ Run Evaluation & Submit All Answers")
+    status_output = gr.Textbox(label="📝 Run Status", lines=5, interactive=False)
+    results_table = gr.DataFrame(label="📋 Results", wrap=True)
+
+    run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
+
+if __name__ == "__main__":
+    print("🚀 Launching Gradio app...")
+    demo.launch(debug=True, share=False)